Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the formula, support for multiple boards, and optional pricing, but does not disclose output format, whether results are aggregated or per-board, rounding behavior, or how unit conversions are handled. This leaves meaningful gaps in predicting tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. It front-loads the core purpose and formula in the first sentence, then adds the key modifiers (multiple boards, optional price, price units) in the second. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 parameters, no output schema, and no annotations, so the description must cover enough for correct invocation. It explains the calculation and pricing options, but does not specify output structure (e.g., totals vs. line items, cost if price omitted). Given the simplicity of the domain and thorough schema coverage, it is acceptable but has clear gaps for an agent expecting detailed return semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents all parameters with 100% coverage, but the description adds meaningful context beyond the schema by explaining the board-foot formula and how price relates to price_unit (per bf or MBF). It clarifies the purpose of the optional price and the multi-board aggregation, adding value over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates board feet and lumber cost, provides the formula (thickness x width x length / 144 in inches), and contrasts with sibling tools by focusing on lumber pricing. This is specific and distinguishable from related calculators like lumber_weight_calculator or log_volume.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for board foot and lumber cost calculations, but it does not explicitly state when to use this tool versus alternatives or provide conditions/exclusions. There is no mention of alternatives or when-not-to-use, leaving the agent to infer applicability.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.